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The Impact of Artificial Intelligence on Chatbot Technology: A Study on the Current Advancements and Leading Innovations

August 2023
European Journal of Technology 7(3):62-72

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University of the Cumberlands

Artificial intelligence (AI) has had a profound impact on various industries, and one prominent domain where its influence is evident is in chatbot technology. Chatbots, computer programs designed to simulate human conversation, have evolved significantly through the advancements in AI, becoming more sophisticated and intelligent. This research paper aims to explore the current state of AI-powered chatbot technology, focusing on the latest advancements and leading innovations. The study delves into the application of natural language processing (NLP) algorithms, machine learning models, and deep learning techniques in chatbot development to gain insights into their capabilities and limitations. The research also highlights leading innovations in AI-powered chatbot technology, such as virtual assistants and voice-enabled chatbots. These conversational agents have transformed various industries, providing innovative solutions to virtual reference services and customer-company interactions. The study delves into the contextual understanding and personalized responses that chatbots can provide, offering tailored interactions to meet users' specific needs and preferences. Furthermore, the integration of other technologies, including speech recognition and sentiment analysis, enhances chatbot capabilities, improving user satisfaction and engagement. However, while AI-powered chatbots have enhanced user experiences, customer satisfaction, and efficiency in industries like customer support and service, they also raise potential ethical and privacy concerns. Medical chatbots, in particular, pose legal and ethical challenges that require careful management and the development of appropriate ethical frameworks. Understanding the advancements, innovations, and impact of AI on chatbot technology is essential for recognizing the potential benefits and challenges these systems present. By addressing ethical and privacy concerns, chatbots can responsibly shape the future of human-computer interactions, further contributing to the broader understanding of AI's role in transforming industries and enhancing user experiences.

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The Impact of Artificial Intelligence on Chatbot

Technology: A Study on the Current

Advancements and Leading Innovations

Farhan Aslam

European Journal of Technology

ISSN 2520-0712 (online)

Vol.7, Issue 2, pp 62 - 72, 2023

www

.ajpojou

nal

The Impact of Artificial Intelligence on Chatbot Technology: A Study

on the Current Advancements and Leading Innovations

Farhan Aslam1*

Department of Information Technology, University of the Cumberlands, KY, USA

Article history

Submitted 06.08.2023 Revised Version Received 13.08.2023 Accepted 15.08.2023

Abstract

Artificial intelligence (AI) has had a profound

impact on various industries, and one

prominent domain where its influence is

evident is in chatbot technology. Chatbots,

computer programs designed to simulate

human conversation, have evolved

significantly through the advancements in AI,

becoming more sophisticated and intelligent.

This research paper aims to explore the current

state of AI-powered chatbot technology,

focusing on the latest advancements and

leading innovations. The study delves into the

application of natural language processing

(NLP) algorithms, machine learning models,

and deep learning techniques in chatbot

development to gain insights into their

capabilities and limitations. The research also

highlights leading innovations in AI-powered

chatbot technology, such as virtual assistants

and voice-enabled chatbots. These

conversational agents have transformed various

industries, providing innovative solutions to

virtual reference services and customer-

company interactions. The study delves into the

contextual understanding and personalized

responses that chatbots can provide, offering

tailored interactions to meet users' specific

needs and preferences. Furthermore, the

integration of other technologies, including

speech recognition and sentiment analysis,

enhances chatbot capabilities, improving user

satisfaction and engagement. However, while

AI-powered chatbots have enhanced user

experiences, customer satisfaction, and

efficiency in industries like customer support

and service, they also raise potential ethical and

privacy concerns. Medical chatbots, in

particular, pose legal and ethical challenges that

require careful management and the

development of appropriate ethical

frameworks. Understanding the advancements,

innovations, and impact of AI on chatbot

technology is essential for recognizing the

potential benefits and challenges these systems

present. By addressing ethical and privacy

concerns, chatbots can responsibly shape the

future of human-computer interactions, further

contributing to the broader understanding of

AI's role in transforming industries and

enhancing user experiences.

Keywords: Artificial Intelligence, Chatbot

Technology, Natural Language Processing,

Machine Learning, Deep Learning, Virtual

Assistants, Voice-Enabled Chatbots

European Journal of Technology

ISSN 2520-0712 (online)

Vol.7, Issue 2, pp 62 - 72, 2023

www

.ajpojou

nal

1.0 INTRODUCTION

Artificial intelligence (AI) has had a profound impact on numerous industries, particularly in the realm

of chatbot technology. Chatbots, which are computer programs designed to simulate human

conversation, have evolved to become more sophisticated and intelligent due to advancements in AI

Purpose

The purpose of this research paper is to explore the current advancements and leading innovations in

AI-powered chatbot technology and examine their impact on various industries. The study aims to

analyze the application of natural language processing (NLP) algorithms, machine learning models,

and deep learning techniques in chatbot technology to gain insights into their capabilities and

limitations.

Additionally, the research will discuss the leading innovations in chatbot technology, such as virtual

assistants and voice-enabled chatbots, contextual understanding, and integration with other

technologies to enhance their capabilities. Furthermore, the paper will investigate the impact of AI-

powered chatbots on user experience, customer satisfaction, efficiency, and cost-effectiveness in

customer support and service industries. The study also recognizes the importance of addressing

potential ethical and privacy concerns associated with AI-powered chatbots to ensure responsible and

secure deployment. By providing a comprehensive analysis of the advancements, innovations, and

impact of AI on chatbot technology, this research contributes to a broader understanding of AI's role

in shaping the future of human-computer interactions.

2.0 METHODOLOGY

The methodology employed for this research involves a comprehensive literature review and analysis

of existing studies and research papers related to AI-powered chatbot technology. The research sources

include peer-reviewed journal articles, conference papers, industry reports, and reputable online

publications. The review encompasses a wide range of topics, such as NLP algorithms, machine

learning models, deep learning techniques, virtual assistants, voice-enabled chatbots, and their

applications in various industries.

To gain insights into the advancements in chatbot technology, the literature review will focus on recent

research published within the last five years. This ensures that the study captures the most up-to-date

developments and trends in the field.

Additionally, the research will conduct case studies and examine real-world deployments of AI-

powered chatbots in different industries to assess their impact on user behavior, organizational

efficiency, and cost-effectiveness. Longitudinal studies and user feedback analysis will be used to

gauge the long-term benefits and challenges of integrating chatbots into various domains.

Furthermore, the study will address ethical and privacy concerns associated with AI-powered chatbots

by reviewing existing ethical frameworks and guidelines proposed by researchers and industry experts.

It will also explore the potential biases and risks that may arise from the use of AI in chatbots and

propose recommendations to address these issues.

Overall, the combination of literature review, case studies, and ethical analysis will provide a

comprehensive and insightful understanding of the current advancements, leading innovations, and

impact of AI-powered chatbot technology in diverse industries. The findings of this research will

contribute to the broader discourse on AI and its transformative effects on human-computer

interactions and various sectors of the economy.

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Recommendation

Based on the findings, it is recommended that stakeholders collaboratively establish robust ethical

frameworks to govern the deployment of AI-powered chatbots, particularly in sensitive domains like

healthcare. The design of chatbots should prioritize user-centric experiences, incorporating transparent

explanations for decisions and fostering inter-agent collaboration. Further research should focus on

multilingual adaptability, bias mitigation, and continuous learning mechanisms. Public awareness

campaigns should be developed to educate users about chatbot interactions. Moreover, researchers and

practitioners are encouraged to engage in collaborative knowledge sharing to advance the responsible

development of AI-powered chatbots across industries.

Problem Statement

The rapid advancement of AI-powered chatbot technology has ushered in transformative possibilities

across industries, yet this progress is accompanied by a series of pressing challenges. As these chatbots

become integral to various sectors, ethical and privacy concerns have emerged, necessitating the

development of robust frameworks to address issues related to data security, transparency, and

accountability. Furthermore, ensuring seamless user experiences and personalized interactions with

chatbots demands innovative solutions to enhance natural language understanding, context-awareness,

and emotional intelligence. Bridging the gap between technological capabilities and ethical

considerations is crucial to harnessing the full potential of AI-powered chatbots while safeguarding

user trust and societal well-being

Current Advancements in AI Powered Chatbot Technology

Natural Language Processing (NLP) Algorithms and Techniques Used in Chatbot Technology

Natural Language Processing (NLP) algorithms and techniques play a crucial role in chatbot

technology, particularly in the field of healthcare. Using NLP, chatbots are able to understand and

interpret user queries, providing appropriate responses and guidance. One of the initial steps in NLP

processing is Natural Language Understanding (NLU), which decodes the semantic meaning of user

input and recognizes morphemes [1]. In the case of chat interfaces, NLU becomes the first level of

processing since there is no audio-to-text conversion. Through NLU, the chatbot is able to detect

entities and map them to respective intents using tools like Dialogflow [1].

The use of NLP algorithms enables the chatbot to mimic human behavior, creating a user-friendly

chat system that can provide primary healthcare education, advice, preventive measures, home

remedies, healthcare tips, symptoms, and location-based diet recommendations [1]. Additionally, NLP

is used to convert user speech to text, allowing for seamless communication between the user and the

European Journal of Technology

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chatbot [1]. By employing NLP algorithms, chatbots are able to adapt to individual language usages,

searches, and preferences, enhancing the overall user experience [1].

With the advancement of technology and the integration of NLP algorithms, voice bots are designed

to have human-like conversations, utilizing Natural User Interfaces and AI-powered interaction

processes that are simple and easy to communicate with users [1]. Overall, NLP algorithms and

techniques are essential in creating conversational interfaces that enhance user engagement and

provide efficient and accurate responses in chatbot technology.

Machine Learning Models and Algorithms for Chatbot Training and Response Generation

In the field of chatbot training and response generation, there is a growing focus on leveraging machine

learning models and algorithms. One approach is to incorporate artificial intelligence (AI) technology

to enhance engagement and customer satisfaction with chatbot services. By integrating theories such

as the elaboration likelihood model (ELM) and technology gratification, researchers aim to develop a

model that links engagement-facilitating technology, like chatbot services, with customer satisfaction

[2][3].

This integration allows for a better understanding of the impact of AI-driven chatbots on user

experience and behavior. For instance, a study collected survey data from consumers who used

chatbots to examine the influence of AI-driven chatbots on user satisfaction [4]. Moreover, the use of

AI-powered chatbots extends beyond customer service applications.

In the field of nursing education, AI-Chatbots have been explored to understand their potential in

enhancing learning experiences [5]. These findings highlight the significance of AI-powered chatbot

technology in various domains. As research continues to investigate the design implications of AI-

powered chatbots, it is clear that the adoption and impact of chatbot technologies are substantial and

comparable to other technological advancements [6].

Overall, the integration of machine learning models and algorithms in chatbot development is crucial

for improving user experiences and maximizing the potential of AI technology in various applications.

Deep Learning Techniques for Improving Chatbot Understanding and Conversation Flow

In the realm of chatbot development, the integration of deep learning techniques has shown promise

in improving understanding and conversation flow. One study focused on boosting chatbot adoption

by building a model that links engagement-facilitating technology with customer satisfaction [2][3].

The aim was to better understand the influence of technology gratification on user satisfaction,

highlighting the importance of creating a positive user experience with AI-powered chatbots [7][6].

Another study explored the use of an AI-powered chatbot called Chat Generative Pre-trained

Transformer (ChatGPT) in nursing education, showcasing the potential of AI-Chatbot technology in

various fields [5]. Additionally, the study targeted customers who had already used chatbot systems,

emphasizing the importance of understanding the customers' virtual flow experience with AI-powered

chatbots [8]. These findings demonstrate the growing interest in leveraging deep learning techniques

to enhance chatbot functionality and improve user interactions.

Leading Innovations in AI Powered Chatbot Technology

Virtual Assistants and Voice-Enabled Chatbots

Virtual assistants and voice-enabled chatbots, powered by artificial intelligence (AI), have

revolutionized various industries and transformed customer-company interactions. These AI-powered

conversational agents offer a newer dimension to virtual reference services, particularly in libraries

[9]. They augment the reference service in libraries, providing a dependable solution for initiating

virtual assistance [9]. Moreover, AI-powered conversational agents have found extensive use in the

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digital transformation of customer-company interactions, particularly in the context of shopping [10].

However, there is still limited understanding of how customers use and resist AI-powered

conversational agents for shopping, highlighting the need for further research on customer motivation,

attitudes, and behavioral intentions towards these technologies [10].

Retail managers and developers can gain valuable insights from such studies to better design and

deploy these technologies and enhance the overall customer experience [10]. Additionally, studies

have focused on both text-based and voice-based chatbots, providing empirical evidence to support

hypotheses driven by behavioral reasoning theory and structural equation modeling [10]. The

emergence of advanced AI tools like ChatGPT has further expanded the potential applications of

conversational agents in various fields, including healthcare, education, finance, entertainment, digital

marketing, and e-commerce [11]. ChatGPT, in particular, has garnered significant attention and

anticipation in marketing due to its convenience, efficiency, and personalization capabilities [11].

However, it is important to note that there are concerns regarding the use of AI-generated text in

scientific work, with limitations on its applicability in research papers and journals [11]. Despite these

considerations, ChatGPT has generated widespread public interest, with individuals eager to

experience its innovation and assess its capabilities [11].

Contextual Understanding and Personalized Responses

The inclusion of NLP and NLU in the design of the conversational bot "Aapka Chikitsak" suggests a

level of contextual understanding and personalized responses. By utilizing semantic analysis, the bot

is able to comprehend user queries and provide appropriate responses based on the detected entities

and intents. This implies that the bot is capable of tailoring its responses to the specific needs and

concerns of the users [11]. Similarly, the automation of tasks previously performed by humans by

ChatGPT indicates its ability to provide personalized responses based on contextual understanding

[11]. Furthermore, the AI-generated posts' capability to suggest hashtags for users demonstrates a level

of contextual understanding and the ability to adapt to individual preferences [11]. In addition,

ChatGPT has the potential to collect and analyze personal data, which suggests that it can further tailor

its responses based on user information [11]. However, it is crucial to ensure that ChatGPT is designed

and tested adequately to avoid perpetuating and amplifying biases, highlighting the importance of

contextual understanding and unbiased responses [11]. Overall, the inclusion of NLP, NLU, and the

ability to automate tasks in these conversational bots indicates their potential for providing

personalized responses based on contextual understanding.

Integration with Other Technologies (E.G., Speech Recognition, Sentiment Analysis) to Enhance

Chatbot Capabilities

Integration with other technologies such as speech recognition and sentiment analysis can greatly

enhance the capabilities of chatbots. These technologies play a crucial role in improving user

satisfaction and overall chatbot adoption. For instance, speech recognition technology allows chatbot

users to interact with the system through voice commands, eliminating the need for manual typing and

enhancing the user experience [12]. Sentiment analysis, on the other hand, enables chatbots to analyze

and understand the emotions and sentiments of users, allowing for more personalized and empathetic

responses. This feature can significantly improve user satisfaction and engagement with the chatbot

[12][17].

One example of an AI-powered chatbot platform that incorporates these technologies is ChatGPT

developed by OpenAI. ChatGPT enables human users to have natural conversations with the chatbot,

leveraging AI technology to provide innovative and interactive experiences [11]. The integration of

speech recognition and sentiment analysis technologies into chatbot platforms like ChatGPT

demonstrates the potential for revolutionizing how people interact with technology and enhancing the

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overall user experience [13]. By incorporating these innovative technologies, chatbot developers can

create more advanced and user-friendly systems that cater to the evolving needs of users in various

industries [14].

Impact of AI on Chatbot Technology

Improved User Experience and Customer Satisfaction

The use of chatbots has become increasingly popular in various industries, contributing to improved

user experience and customer satisfaction. One reason for this is that chatbots present an air of

authority and sound trustworthy, which enhances the overall user experience and instills confidence in

customers [15]. Additionally, chatbots offer convenience and efficiency, which are highly valued by

users, leading to enhanced customer satisfaction [15]. The popularity of chatbots itself is indicative of

their positive impact on user experience, as users perceive them as friendly companions that bring

them closer to interacting with a brand or service [15][16]. Moreover, chatbots have the ability to

detect and respond to users' emotional requests, further improving the overall user experience and

customer satisfaction [16].

Another factor contributing to improved user experience is the scalability of chatbots, as they can

handle multiple users simultaneously, leading to faster response times and a seamless user experience

[16]. Furthermore, the integration of different chatbots, such as the example of Alexa-Cortana

integration, enables inter-agent communication and can contribute to an improved user experience and

customer satisfaction [16]. Intrapersonal chatbots, such as chat apps like Messenger, Slack, and

WhatsApp, also enhance user experience by acting as companions and understanding users like

humans do [16]. Similarly, interpersonal chatbots that offer services such as restaurant booking and

flight booking can provide an improved user experience and customer satisfaction [16][17].

Overall, the use of chatbots in various contexts and their ability to enhance user experiences through

features like trustworthiness, convenience, emotional response, scalability, inter-agent

communication, and personalized services contribute to increased customer satisfaction.

Increased Efficiency and Cost-Effectiveness in Customer Support and Service Industries

Advancements in technology have revolutionized various industries, including customer support and

service. Just as digital cameras disrupted the photography market by offering a more convenient and

cost-effective alternative to film cameras [15], the use of advanced chatbot systems like ChatGPT has

the potential to significantly increase efficiency and cost-effectiveness in the customer support and

service industries. For instance, in the healthcare industry, ChatGPT has been explored as a

professionally trained medical chatbot that could reduce medical errors and improve patient care [15].

This could be achieved through its ability to operate quickly and provide accurate information,

potentially saving healthcare providers time and resources [15]. Moreover, ChatGPT has the capability

to draw on a larger database, which could enhance the effectiveness of customer support and service

industries by providing more comprehensive and accurate responses to customer inquiries [15]. By

leveraging these technological advancements, organizations can streamline their operations, improve

customer satisfaction, and achieve cost savings in the long run [17].

Potential Ethical and Privacy Concerns Associated with AI-Powered Chatbots

The integration of AI in chatbots raises potential ethical and privacy concerns. Medical chatbots, in

particular, have presented legal and ethical challenges that need to be addressed and managed [15].

Developing ethical frameworks for AI-powered chatbots requires negotiation among various

stakeholders, especially regarding patient data ownership [15]. However, the deployment of these

frameworks is not keeping pace with the rapid advancement of AI-powered chatbots like ChatGPT

[15]. While chatbots like ChatGPT have strengths in natural language processing and information

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extraction from unstructured data sources, they were not trained by specialized medical professionals

and may lack accuracy compared to medical chatbots developed by dedicated medical professionals

[15]. Despite their potential to reduce the workload of frontline health workers during routine medical

checks, ethical and privacy concerns persist in the widespread use of AI-powered chatbots [15]. These

concerns encompass issues such as data content, cybersecurity, privacy, patient safety, trust, and

transparency [15]. As AI-powered chatbots become increasingly integrated into our daily lives, it is

crucial to address these ethical and privacy concerns to ensure the responsible and secure use of this

technology [16].

Further Research

The study presented here provides valuable insights into the impact of artificial intelligence on chatbot

technology, highlighting its current advancements, leading innovations, and implications across

various industries. However, several areas remain ripe for further research to deepen our understanding

and capitalize on the potential of AI-powered chatbots. The following are some key areas that warrant

further investigation:

1. Ethical and Privacy Concerns: As AI-powered chatbots continue to gain prominence in

various domains, addressing ethical and privacy concerns is of paramount importance. Further

research should focus on developing comprehensive ethical frameworks to govern the use of

AI-powered chatbots, particularly in sensitive fields like healthcare and finance. Examining the

implications of data ownership, cybersecurity, and ensuring transparent and responsible AI

deployment will be crucial in fostering user trust and mitigating potential risks.

2. User Experience and Interaction Design: While chatbots have shown promise in enhancing

user experiences, further research is needed to optimize their interaction design. Studying the

impact of chatbot personalities, tone, and language style on user engagement and satisfaction

can inform the development of more user-friendly and emotionally intelligent chatbot

interfaces. Additionally, investigating user preferences and expectations in different industries

and scenarios can lead to tailored chatbot designs that cater to diverse user needs.

3. Deep Learning Techniques and Natural Language Understanding: Deep learning has

significantly improved chatbot capabilities, but there is still scope for advancing natural

language understanding and conversation flow. Research should explore novel deep learning

architectures and techniques to enhance chatbot comprehension of context and improve the

generation of contextually relevant responses. Additionally, integrating external knowledge

sources and real-time contextual awareness can contribute to more sophisticated and dynamic

chatbot interactions.

4. Inter-Agent Communication and Collaboration: Investigating the possibilities of inter-

agent communication and collaboration between multiple chatbots or virtual assistants holds

great potential for creating seamless and comprehensive user experiences. Research in this area

can pave the way for a networked ecosystem of chatbots that work collaboratively to provide

users with integrated and holistic support across various domains.

5. User Trust and Explainability: Enhancing user trust in AI-powered chatbots is crucial for

widespread adoption. Research should explore methods to make chatbot decision-making

processes more transparent and interpretable to users. Designing chatbots with the ability to

provide explanations for their actions and recommendations can help build user confidence and

acceptance.

6. Domain-Specific Applications: While chatbots have found utility in multiple industries,

further research can focus on domain-specific applications, such as education, entertainment,

and mental health support. Investigating how chatbots can effectively cater to the unique

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requirements and challenges of these domains can unlock new possibilities for personalized

and specialized services.

7. Multilingual and Cross-Cultural Chatbots: Developing chatbots capable of handling

multiple languages and understanding cross-cultural nuances will be crucial in a globalized

world. Further research should explore techniques for building multilingual chatbots that can

offer seamless interactions and culturally sensitive responses to users from diverse linguistic

backgrounds.

8. Real-World Deployments and Impact: Conducting large-scale real-world deployments of

AI-powered chatbots and analyzing their impact on user behavior, organizational efficiency,

and cost-effectiveness will provide valuable insights. Longitudinal studies and user feedback

analysis can help gauge the long-term benefits and challenges of integrating chatbots into

different industries.

3.0 CONCLUSION

The impact of artificial intelligence (AI) on chatbot technology has been a subject of significant

research and development, as evident in this study. The utilization of Natural Language Processing

(NLP) algorithms and techniques in chatbot technology, particularly in the healthcare domain, has

proven crucial in enabling chatbots to understand and interpret user queries effectively. The integration

of NLP algorithms allows for seamless communication between the user and the chatbot, as it converts

user speech to text. This feature, combined with Natural Language Understanding (NLU) processing,

facilitates the decoding of the semantic meaning of user input and recognition of morphemes. The

ability of chatbots to mimic human behavior and provide primary healthcare education, advice,

preventive measures, and healthcare tips highlights their potential to enhance user engagement and

provide accurate responses. However, the deployment of AI-powered chatbots has raised ethical and

privacy concerns, necessitating the development of ethical frameworks to address these issues.

The integration of AI technology in chatbot services has the potential to enhance engagement and

customer satisfaction, but it is crucial to ensure that the deployment of such frameworks keeps pace

with the rapid advancement of AI-powered chatbots. Furthermore, the use of NLP algorithms enables

chatbots to adapt to individual language usages, searches, and preferences, thereby improving user

satisfaction and overall chatbot adoption. The application of AI-powered chatbots extends beyond

customer service, finding utility in virtual reference services, such as libraries. Nonetheless, the

development of accurate and reliable medical chatbots requires specialized medical professionals'

involvement to ensure accuracy and mitigate potential risks.

It is essential to acknowledge the limitations and gaps in current research, particularly in the ethical

and privacy aspects of AI-powered chatbots. Future research should focus on developing a model that

links engagement-facilitating technology, like chatbots, with customer satisfaction and behavior, using

established theoretical frameworks. Additionally, efforts should be made to address the challenges

related to patient data ownership and privacy concerns associated with the widespread use of AI-

powered chatbots. Overall, advancements in AI technology have revolutionized various industries,

including customer support and service, and the ongoing research in this area continues to contribute

to the enhancement of chatbot functionality and user interactions.

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May 2025

Citation: Gao, J.; Agarwal, R.; Garsole, P. AI Testing for Intelligent Chatbots-A Case Study. Software 2025, 4, 12. https://doi. Abstract: The decision tree test method works as a flowchart structure for conversational flow. It has predetermined questions and answers that guide the user through specific tasks. Inspired by principles of the decision tree test method in software engineering, this paper discusses intelligent AI test modeling chat systems, including basic concepts, quality validation, test generation and augmentation, testing scopes, approaches, and needs. The paper's novelty lies in an intelligent AI test modeling chatbot system built and implemented based on an innovative 3-dimensional AI test model for AI-powered functions in intelligent mobile apps to support model-based AI function testing, test data generation, and adequate test coverage result analysis. As a result, a case study is provided using a mental health and emotional intelligence chatbot system, Wysa. It helps in tracking and analyzing mood and helps in sentiment analysis.

Artificial Intelligence in Sustainable Industrial Transformation: A Comparative Study of Industry 4.0 and Industry 5.0

Article

Full-text available

May 2025

Industry 4.0 continues to progress due to the implementation of artificial intelligence (AI), which enables the automation of operations and complex big data exploitation to improve production efficiency. Industry 5.0 emerged to tackle sustainability issues and ensure human focus because Industry 4.0 followed a profit-maximizing strategy that raised important concerns. This comparative study fills the knowledge gap about how AI contributes to Industry 5.0 sustainability by studying its differences from Industry 4.0. This review investigates how AI enables circular economy principles through a systematic literature review while studying its impact on industrial resilience and adaptive manufacturing capabilities. This study underscored that Industry 5.0 uses AI to unite human creativity with modern technologies , enabling sustainable operations and new developments. Data privacy, cybersecurity, and algorithmic bias remain persistent issues in the current context. This review found that AI-based systems implementation in Industry 5.0 led to a 30% boost in resource utilization compared to the Industry 4.0 approach and a 25% decrease in carbon emissions. These findings indicate that ethical AI frameworks must be the priority for policymakers and industries to achieve such technological development while keeping companies' training in mind at the same time. The study establishes that AI is the fundamental technology to shift manufacturing toward a sustainable and human-controlled Industry 5.0 format that establishes resilient green industrial environments. The research develops the academic discussion about using AI to achieve sustainable industrial development.

Guest-Centric AI: A Theoretical Inquiry of Guest Experiences on the Integration of AI Chatbots Among Luxury Guest Accommodations

Chapter

May 2025

Luxury hotels prioritise exceptional, personalised service. Recently, the industry has seen a rise in the use of robots to enhance customer experiences, particularly through efficient check-ins. Consumers have responded positively, expecting more AI-driven services in luxury hotels. AI chatbots are becoming central to operations, helping guests with inquiries, room service, and travel guidance. However, research on AI chatbot features, such as adaptability, responsiveness, and reliability, remains limited, especially in the luxury hotel sector. Additionally, the influence of information quality (e.g. relevance, security, and privacy) on customer satisfaction and intention to continue using these services is underexplored. While AI chatbots have been studied in education, banking, and healthcare, their role in hospitality requires further investigation. This chapter develops a conceptual framework through a systematic review of relevant academic theories, focusing on the factors shaping guest experiences with AI in luxury hotels. By critically evaluating these theories, the chapter aims to enhance understanding of the relationship between AI technologies and guest satisfaction within luxury accommodations.

AI CHATBOTS INTEGRATION IN ONLINE SHOP IN NUEVA ECIJA, PHILIPPINES: STUDY UTILIZING THE EXPECTATION CONFIRMATION THEORY AND ISO/IEC 25010 CRITERIA

Article

Full-text available

Apr 2025

Artificial Intelligence (AI) is transforming E-commerce by enhancing customer relations. In the Philippines, where E-commerce is growing rapidly, understanding the impact of AI integration on online shops is crucial. This study explores consumer satisfaction and acceptance of AI chatbots in online shops, using Expectation Confirmation Theory and ISO/IEC 25010 criteria to evaluate user experience. The study aims to provide insights for E-commerce businesses to optimize AI adoption and improve customer engagement. A self-made questionnaire was employed as the primary data collection tool, with 392 respondents selected through simple random sampling. Findings indicate that online shoppers' expectations align with their current experiences with AI chatbots, as evidenced by positive evaluations of functional suitability, performance efficiency, and usability. These results encourage continued use of AI chatbots, highlighting their effectiveness in addressing customer queries promptly and accurately. The study also notes emerging trends in the online marketplace, with growing demand for toys and baby products, while Fashion, Beauty, and Personal Care items remain dominant. AI chatbots are shown to enhance user experience, making them a strategic asset for E-commerce businesses in the Philippines. Leveraging these insights, businesses can better align with consumer needs and stay competitive in the evolving market.

Bibliometric exploration of artificial intelligence applications in healthcare: trends and future directions

Article

Full-text available

Apr 2025

This research employs the PRISMA framework to conduct an extensive bibliometric analysis, delving into the dynamic realm of Artificial Intelligence (AI) within the healthcare domain. Spanning the years 2010 to 2023, the study systematically gathers and examines scholarly works to delineate the trends, patterns, and emerging topics about AI's integration into healthcare. A thorough initial screening yields substantial academic articles, conference papers, and reviews, forming the basis for analysis. The examination primarily focuses on quantifying publication patterns, identifying influential authors, institutions, and countries, and mapping the thematic landscape of AI in healthcare. Employing various bibliometric metrics such as publication trends, prolific authors, influential journals, and co-occurrence networks of keywords, the study uncovers the remarkable surge in research centred on AI-driven healthcare. This surge signifies a notable paradigm shift towards harnessing technology for predictive analytics, personalized medicine, and enhanced patient care. Additionally, by leveraging visualization tools like VOSviewer, the study presents informative graphical representations elucidating clusters and associations among keywords, thereby providing deeper insights into the interdisciplinary dimensions of AI in healthcare. This study provides a structured overview of the evolving landscape of AI in healthcare, providing valuable perspectives for researchers, practitioners, and policymakers aiming to harness the potential of AI for advancing healthcare delivery and outcomes. The implications of these findings underscore the transformative potential of AI technologies in revolutionizing healthcare delivery, promoting sustainable healthcare practices, and fostering innovative solutions for future challenges.

Hybrid LSTM–Seq2Seq Models: Improved Patient Interaction for Healthcare Chatbots

Article

Full-text available

Apr 2025

Healthcare chatbots play a critical role in improving communication between patients and healthcare providers by offering accurate and timely responses. A novel approach is proposed, which leverages a deep learning model that combines long short-term memory (LSTM) neural networks and a sequence-to-sequence (Seq2Seq) architecture to enhance text prediction accuracy in medical dialogue systems. The model leverages the capability of LSTM to capture long dependencies in sequential data alongside the contextual encoding of Seq2Seq, which improves predictive quality in dialogue responses. The encoder–decoder architecture, which utilizes tokenization and padding to standardize input sequences, contributes to the improvement in data processing. The validation accuracy of the model is 0.9766, with a loss of 0.0184. Specifically, the precision is 0.9961, the recall is 0.9981, and the F1 score is 0.9971. The capability of the model for sequence prediction is attributed to its robustness. Other methods of evaluation employing measures such as the Nash–Sutcliffe efficiency coefficient, correlation coefficient, and normalized root mean square error demonstrate that the model is superior to other machine learning algorithms utilizing linear regression and GP regression. Employing callback functions during training ensures the best-fit model is saved, which makes the method viable in different tasks described in the job descriptions.

Exploring the impact of artificial intelligence-enabled decision aids in improving patient inclusivity, empowerment, and education in urology: a systematic review by EAU endourology

Article

May 2025
CURR OPIN UROL

Purpose of review The implementation of artificial intelligence (AI) in urology has the potential to enhance patient outcomes through the provision of intelligent tools, such as AI-enabled decision aids (AIDAs), which can support personalized care. The objective of this systematic review is to determine the role of AIDAs in educating and empowering patients, particularly those from underrepresented populations. Recent findings We conducted a comprehensive systematic review following PRISMA guidelines to explore the potential for AIDAs to address healthcare inequalities and promote patient education and empowerment. From 1078 abstracts screened, 21 articles were suitable for inclusion, all of which utilized chatbots. Three main themes of studies were identified. Fourteen studies focused on enhancing patient education, four studies investigated whether chatbots can improve the accessibility of urological literature and three studies explored chatbots role in providing lifestyle guidance. While chatbots demonstrated great potential as educational and lifestyle support tools, current research found mixed accuracy and a tendency for them to produce unreliable information. In terms of accessibility, chatbots were able to effectively enhance readability and translate literature, potentially bridging language, and literacy barriers. Summary Through chatbots, AIDAs show strong potential to enhance urological education and empower underrepresented communities. However, chatbots must show greater consistency in accuracy before they can be confidently relied upon in clinical contexts. Further research evaluating chatbots’ efficacy in clinical settings, especially with underrepresented groups, would enable greater understanding of their role in improving patient inclusivity, empowerment, and education.

Revolutionizing E-Commerce Customer Support: Advanced AI-Powered Chatbots for Enhanced User Experience & Operational Efficiency

Conference Paper

Mar 2025

Chatbot Development

Article

Jan 2025

Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI

Article

Full-text available

Apr 2025

Cardiovascular disease (CVD) is rising as a significant concern for the healthcare sector around the world. Researchers have applied multiple traditional approaches to making healthcare systems find new solutions for the CVD concern. Artificial Intelligence (AI) and blockchain are emerging approaches that may be integrated into the healthcare sector to help responsible and secure decision-making in dealing with CVD concerns. Secure CVD information is needed while dealing with confidential patient healthcare data, especially with a decentralized blockchain technology (BCT) system that requires strong encryption. However, AI and blockchain-empowered approaches could make people trust the healthcare sector, mainly in diagnosing areas like cardiovascular care. This research proposed an explainable AI (XAI) approach entangled with BCT that enhances healthcare interpretability and responsibility to cardiovascular health medical experts. XAI is significant in addressing cardiovascular prediction issues and offers potential solutions for complex communication and decision-making in cardiovascular care. The proposed approach performs better, with the highest accuracy of 97.12% compared to earlier methods. This achievement shows its ability to tackle complex issues, accessible during healthcare sector communication and decision processes.

The Benefits and Challenges of Customization within SaaS Cloud Solutions

Article

Full-text available

Jul 2023

Farhan Aslam

Purpose: Software as a Service (SaaS) cloud solutions have gained popularity due to their scalability, cost-effectiveness, and ease of deployment. Customization within SaaS offerings allows businesses to tailor applications to meet their specific needs, enhancing user experiences and overall efficiency. This article examines the benefits and challenges of customization within SaaS cloud solutions. We explore how customization empowers organizations to address unique requirements, streamline workflows, and gain a competitive edge. Additionally, we discuss the potential drawbacks, such as increased maintenance complexity and integration issues. Understanding the balance between customization and standardization is crucial for maximizing the value of SaaS cloud solutions. Methodology: The methodology adopted in this article presents a comprehensive approach to exploring the benefits and challenges of customization within SaaS offerings. The article's structure covers various aspects, including the introduction, benefits of customization, addressing unique business requirements, streamlining workflows, and processes, competitive advantage, challenges of customization, and the importance of balancing customization and standardization. The introduction sets the context for the article, highlighting the increasing adoption of SaaS cloud solutions and the importance of customization in addressing unique business needs. The objectives of the article are clearly defined, focusing on discussing the benefits and challenges associated with customization within SaaS offerings. The section on "The Benefits of Customization in SaaS Cloud Solutions" explores the advantages of customization, such as improved user satisfaction, increased productivity, and competitive differentiation. Real-world examples and research publications are cited to support the benefits of customization. The subsequent section on "Addressing Unique Business Requirements" delves into the significance of customization in meeting specific business needs and industry regulations. The advantages of customization in tailoring SaaS applications to individual customers' requirements are emphasized, leading to increased customer satisfaction. The section on "Streamlining Workflows and Processes" highlights how customization allows businesses to optimize efficiency, reduce manual efforts, and automate repetitive tasks. The customization's role in providing tailored reporting and analytics capabilities to improve decision-making is discussed. Furthermore, the article explores the competitive advantage and market differentiation achieved through customization. By offering unique features and functionalities, businesses can attract and retain customers, leading to increased market share and growth opportunities. The section on "Challenges of Customization in SaaS Cloud Solutions" addresses potential issues like increased complexity in application maintenance, security vulnerabilities, and difficulties in seamless integration with other systems. Various research publications are cited to underscore the challenges faced in SaaS customization. The final section on "Balancing Customization and Standardization" emphasizes the importance of striking a balance between customization and standardization to optimize the benefits of customization while maintaining a sustainable solution. Real-world case studies and research publications are provided to support this concept. The "Results and Discussion" section includes real-world case studies to demonstrate the outcomes of customization initiatives and their impact on business operations. The case studies provide valuable insights into the benefits and challenges of customization within SaaS cloud solutions. In conclusion, the article's methodology is well-structured and supported by research publications, real-world examples, and case studies. The comprehensive exploration of the benefits and challenges of customization within SaaS offerings provides valuable insights for businesses and researchers in the field of cloud computing and software as a service. Findings: The article highlights that customization within SaaS cloud solutions provides several benefits for businesses, including improved user satisfaction, increased productivity, and competitive differentiation. Customization allows organizations to address unique business requirements, streamline workflows, and automate repetitive tasks, leading to cost savings and enhanced efficiency. Real-world case studies support these findings and demonstrate the impact of customization initiatives on business operations and customer satisfaction. However, the article also identifies several challenges associated with customization in SaaS. These challenges include increased maintenance complexity, potential security vulnerabilities, difficulties in seamless integration with other systems, and the need for careful consideration of customization strategies. Addressing these challenges is crucial for successful SaaS customization and to ensure that the benefits are maximized while avoiding potential drawbacks. Recommendations: Based on the findings, the article recommends that businesses carefully evaluate their customization needs and strike a balance between customization and standardization. Over-customization should be avoided to prevent unnecessary complexity and maintenance costs. Instead, businesses should focus on leveraging customization to meet specific business requirements and enhance user experiences effectively. To ensure successful SaaS customization, businesses should prioritize security and consider scalability, vendor selection, and customer-driven management. Engaging in comprehensive planning and involving tenants in the customization process can lead to better outcomes. Additionally, businesses should consider the use of cloud-specific standards and be mindful of the implications of vendor lock-in when making customization decisions. Furthermore, SaaS providers should encourage tenant involvement in the Software Development Life Cycle (SDLC) to capture customization requirements early on and ensure smooth development and integration. It is also crucial to implement adequate security measures to protect tenant data and ensure privacy in multi-tenant environments. By adopting a balanced approach to customization and standardization, businesses can harness the full potential of SaaS cloud solutions, enhance their competitive edge, and achieve optimal outcomes in the cloud environment.

Nursing education in the age of artificial intelligence powered Chatbots (AI-Chatbots): Are we ready yet?

Article

Full-text available

Jul 2023
NURS EDUC TODAY

This article discusses the challenges and implications of artificial intelligence powered chatbot (AI-Chatbots) in nursing education. Chat Generative Pre-trained Transformer (ChatGPT) is an AI-Chatbot that can engage in detailed dialog and pass qualification tests in various fields. It can be applied for drafting course materials and administrative paperwork. Students can use it for personalized self-paced learning. AI-Chatbot technology can be applied in problem-based learning for hands-on practice experiences. There are concerns about over-reliance on the technology, including issues with plagiarism and limiting critical thinking skills. Educators must provide clear guidelines on appropriate use and emphasize the importance of critical thinking and proper citation. Educators must proactively adjust their curricula and pedagogy. AI-Chatbot technology could transform the nursing profession by aiding and streamlining administrative tasks, allowing nurses to focus on patient care. The use of AI-Chatbots to socially assist patients and for therapeutic purposes in mental health shows promise in improving well-being of patients, and potentially easing shortage and burnout for healthcare workers. AI-Chatbots can help nursing students and researchers to overcome technical barriers in nursing informatics, increasing accessibility for individuals without technical background. AI-Chatbot technology has potential in easing tasks for nurses, improving patient care, and enhancing nursing education.

Marketing with ChatGPT: Navigating the Ethical Terrain of GPT-Based Chatbot Technology

Article

Full-text available

Apr 2023

ChatGPT is an AI-powered chatbot platform that enables human users to converse with machines. It utilizes natural language processing and machine learning algorithms, transforming how people interact with AI technology. ChatGPT offers significant advantages over previous similar tools, and its potential for application in various fields has generated attention and anticipation. However, some experts are wary of ChatGPT, citing ethical implications. Therefore, this paper shows that ChatGPT has significant potential to transform marketing and shape its future if certain ethical considerations are taken into account. First, we argue that ChatGPT-based tools can help marketers create content faster and potentially with quality similar to human content creators. It can also assist marketers in conducting more efficient research and understanding customers better, automating customer service, and improving efficiency. Then we discuss ethical implications and potential risks for marketers, consumers, and other stakeholders, that are essential for ChatGPT-based marketing; doing so can help revolutionize marketing while avoiding potential harm to stakeholders.

Does Artificial Intelligence Satisfy You? A Meta-Analysis of User Gratification and User Satisfaction with AI-Powered Chatbots

Article

Full-text available

Sep 2022

While artificial intelligence (AI) has been increasingly employed in communication technologies, limited research has explored the user experience of AI-powered chatbots. Based on Uses & Gratification (U&G) theory, this study conducted a quantitative meta-analysis of 12 studies to examine the relationship between four dimensions of user gratification (utilitarian, technology, hedonic, and social) and user satisfaction with AI-powered chatbots. The results indicate that these four categories of gratifications are strongly associated with user satisfaction to different extents, with utilitarian gratification having the strongest factor influence. The findings suggest that utility is the core aspect of consideration for the designers of AI-powered chatbots. The results further extend the existing U&G literature in the context of AI.

Adapting intelligent information services in libraries: a case of smart AI chatbots

Article

Full-text available

Jan 2022
Libr Hi Tech News

Purpose The recent COVID-19 pandemic affects all segments of the population in all possible fields of life. To encounter this critical situation and to safeguard the health of the library users & library staff, the library services have been forced to adapt and accept the “new normal” and give a greater use and reliance on virtual space than ever before with physical spaces. This paper aims to demonstrate an artificial intelligence (AI)-driven solution that can be practically implemented in the form of a “InfoBot” or “Chatbot” to fulfil user needs 24/7 with minimal or without human intervention. Design/methodology/approach To give a general overview of the use of AI Chatbot in libraries and its multitasking features followed by the practical implementation, a versatile AIchatbot service, Engati is used as a target bot with its basic free plan. Findings The study findings reveal that AI Chatbots offer a dependable solution for the libraries to initiate virtual assistance, thus augmenting the reference service while adding a newer dimension to virtual reference service. Social implications Innovative and intelligent information service would be overcoming the time and location barriers reaffirming the concept of “library without walls” while falling in line with the five laws of library science as propounded by Dr S.R. Ranganathan, the father of library science in India. Originality/value Though the implementation of bots and chatbots is not a purely novel concept to explore, no such research has been conducted focusing particularly on its exceptional benefits in the library in reference to the recent pandemic.

An Overview of Chatbot Technology

Conference Paper

Full-text available

May 2020

The use of chatbots evolved rapidly in numerous fields in recent years, including Marketing, Supporting Systems, Education, Health Care, Cultural Heritage, and Entertainment. In this paper, we first present a historical overview of the evolution of the international community’s interest in chatbots. Next, we discuss the motivations that drive the use of chatbots, and we clarify chatbots’ usefulness in a variety of areas. Moreover, we highlight the impact of social stereotypes on chatbots design. After clarifying necessary technological concepts, we move on to a chatbot classification based on various criteria, such as the area of knowledge they refer to, the need they serve and others. Furthermore, we present the general architecture of modern chatbots while also mentioning the main platforms for their creation. Our engagement with the subject so far, reassures us of the prospects of chatbots and encourages us to study them in greater extent and depth.

Tell Me About Yourself: Using an AI-Powered Chatbot to Conduct Conversational Surveys with Open-Ended Questions

Preprint

Full-text available

Mar 2020

The rise of increasingly more powerful chatbots offers a new way to collect information through conversational surveys, where a chatbot asks open-ended questions, interprets a user's free-text responses, and probes answers whenever needed. To investigate the effectiveness and limitations of such a chatbot in conducting surveys, we conducted a field study involving about 600 participants. In this study with mostly open-ended questions, half of the participants took a typical online survey on Qualtrics and the other half interacted with an AI-powered chatbot to complete a conversational survey. Our detailed analysis of over 5200 free-text responses revealed that the chatbot drove a significantly higher level of participant engagement and elicited significantly better quality responses measured by Gricean Maxims in terms of their informativeness, relevance, specificity, and clarity. Based on our results, we discuss design implications for creating AI-powered chatbots to conduct effective surveys and beyond.

Inducing AI-powered chatbot use for customer purchase: the role of information value and innovative technology

Article

Jun 2023
J Syst Inform Tech

Xuan Cu Le

Purpose This study aims to understand a customer-purchase mechanism in the artificial intelligence (AI)-powered chatbot context based on the elaboration likelihood model (ELM) and technology acceptance model (TAM). The first objective is to examine how to boost chatbot adoption. The second objective is to investigate the role of information characteristics, technology-related characteristics and attitude toward AI in purchase intention. Design/methodology/approach Data was collected from a sample of 492 users in Vietnam, who are potential customers of chatbots for purchase. Structural equation modeling was applied for data analysis. Findings Results illustrate that chatbot adoption is significantly influenced by information credibility, technology-related factors (i.e. interactivity, relative advantage and perceived intelligence), attitude toward AI and perceived usefulness. Moreover, information quality and persuasiveness motivate information credibility. Information credibility and attitude toward AI are the essential motivations for perceived usefulness. Finally, chatbot adoption and information credibility determine purchase intention. Practical implications The results are insightful for practitioners to envisage the importance of chatbot use for customer purchase in the AI scenario. Additionally, this research offers a framework to practitioners for shaping customer engagement in chatbots. Originality/value The value of this work lies in the incorporation of technology-related characteristics into the two well-established theories, the ELM and TAM, to identify the importance of AI and its applications (i.e. chatbots) for purchase and to understand the formation of perceived usefulness and chatbot use through information credibility and attitude toward AI.

Virtual agents and flow experience: An empirical examination of AI-powered chatbots

Article

Aug 2022
TECHNOL FORECAST SOC

The aspects that could shape customers' virtual experiences with chatbot applications are poorly understood. Therefore, this study aims to empirically examine the main factors that shape customers' virtual flow experiences with AI-powered chatbots. The conceptual model was based on flow theory and the technology interactivity model. This model was extended to include the impact of both readability and transparency. The data were collected using an online questionnaire survey posted to 500 customers of courier, package delivery, and express mail services. The statistical results largely supported the role of readability, transparency, personalisation, responsiveness, and ubiquitous connectivity in shaping the virtual flow experience with chatbots, which in turn has a significant impact on both communication quality and satisfaction. This study opens new horizons for researchers and practitioners to consider dimensions other than satisfaction and intention to use, to facilitate and accelerate the pace of success of chatbot applications. However, several areas have not been fully addressed in the current study which could be worth considering in future research, as discussed in the related subsection.

AI-powered chatbot communication with customers: Dialogic interactions, satisfaction, engagement, and customer behavior

Article

May 2022
COMPUT HUM BEHAV

The present study is grounded in social exchange theory and resource exchange theory. By exploring customers' satisfaction with chatbot services and their social media engagement, it examined the effects of responsiveness and a conversational tone in dialogic chatbot communication on customers. To test the proposed mediation model, we surveyed a representative sample of customers (N = 965) living in the U.S. After examining the validity and reliability of our measurement model, we tested the hypothesized model using structural equation modeling (SEM) procedures. All proposed hypotheses were supported, indicating the significant direct effects of (1) responsiveness and a conversational tone on customers' satisfaction with chatbot services, (2) customers' chatbot use satisfaction on social media engagement, (3) customers’ social media engagement on price premium and purchase intention, and (4) purchase intention on price premium. In addition, we examined satisfaction, social media engagement, and purchase intention as significant mediators in the proposed model. Theoretical and practical implications of the study were then discussed.

The Impact of Artificial Intelligence on Chatbot Technology: A Study on the Current Advancements and Leading Innovations

Abstract

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